Title
Spectral Constrained Frequency Selective Extrapolation for Rapid Image Error Concealment
Abstract
High quality error concealment plays a crucial role in image and video processing. In general, those algorithms introduce a high computational load as they calculate complex models to estimate the missing samples. In the following, a highspeed algorithm is introduced, which succeeds the state-of-the-art Frequency Selective Extrapolation. Therefore, two novel spectral constraints are introduced in this paper. Firstly, processing the DC part of the distorted spectrum separately allows to decrease computational complexity and to increase the reconstruction quality. Secondly, by exploiting spectral properties, only a subset of basis functions has to be processed. Moreover, complex-conjugated pairs of basis functions are selected to generate a symmetric Fourier spectrum and an according real-valued output signal. Taking these constraints into account, a PSNR gain of up to 0.36 dB is achieved compared to the state-of-the-art algorithm, while the execution speed is approximately doubled.
Year
DOI
Venue
2018
10.1109/IWSSIP.2018.8439150
2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP)
Keywords
Field
DocType
Error Concealment,Inpainting,Signal Extrapolation
Spectral properties,Error concealment,Video processing,Pattern recognition,Computer science,Inpainting,Extrapolation,Artificial intelligence,Basis function,Fourier spectrum,Computational complexity theory
Conference
ISSN
ISBN
Citations 
2157-8672
978-1-5386-6980-8
2
PageRank 
References 
Authors
0.39
5
3
Name
Order
Citations
PageRank
Nils Genser132.45
Jürgen Seiler214528.28
André Kaup3861127.24